DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 05/28/2026 has been entered.
Application Status
This office action is responsive to the claim amendments filed on 05/28/2026.
This action has been made NON-FINAL.
35 U.S.C. 112(f) or 35 U.S.C. 112 (pre-AIA ), sixth paragraph
Claim Interpretations
Claim limitation “means for receiving” and “means for processing” have been interpreted under 35 U.S.C. 112(f) or 35 U.S.C. 112 (pre-AIA ), sixth paragraph, because they use non-structural terms “means” coupled with functional language “receiving” and “processing,” etc., without reciting sufficient structure to achieve the function. Furthermore, the non-structural term is not preceded by a structural modifier. Since this claim limitation invokes 35 U.S.C. 112(f) or 35 U.S.C. 112 (pre-AIA ), sixth paragraph, claim 20 is interpreted to cover the corresponding structure described in the specification that achieves the claimed function, and equivalents thereof.
A review of the specification shows that the following appears to be the corresponding structure described in the specification for the 35 U.S.C. 112(f) or 35 U.S.C. 112 (pre-AIA ), sixth paragraph limitation: pars. 0142 and Fig. 18.
If applicant wishes to provide further explanation or dispute the examiner’s interpretation of the corresponding structure, applicant must identify the corresponding structure with reference to the specification by page and line number, and to the drawing, if any, by reference characters in response to this Office action.
If applicant does not wish to have the claim limitation treated under 35 U.S.C. 112(f) or 35 U.S.C. 112 (pre-AIA ), sixth paragraph, applicant may amend the claim so that it will clearly not invoke 35 U.S.C. 112(f) or 35 U.S.C. 112 (pre-AIA ), sixth paragraph, or present a sufficient showing that the claim recites sufficient structure, material, or acts for performing the claimed function to preclude application of 35 U.S.C. 112(f) or 35 U.S.C. 112 (pre-AIA ), sixth paragraph.
For more information, see MPEP § 2173 et seq. and Supplementary Examination Guidelines for Determining Compliance with 35 U.S.C. § 112 and for Treatment of Related Issues in Patent Applications, 76 FR 7162, 7167 (Feb. 9, 2011).
Response to Arguments
Applicant's arguments filed 05/28/2026 have been fully considered but they are not persuasive.
The Applicant alleged the following on pages 9-10 of the remarks: “Neither reference, alone or in combination, discloses or suggests a system in which the user types ordinary chat text-text the user is composing for the purpose of sending to another human as a chat message-and the system routes that same chat text into a generative language model via a predefined prompt template to obtain a textual description, and then into a generative image model via a second predefined prompt template to obtain a custom sticker presented in association with the message in the chat interface. The amended claims thus recite an arrangement that is absent from Mahar, absent from Davidson, and absent from any cited combination.” The examiner is not persuaded. Paragraph 0096 of Mahar clearly discloses “During the template creation phase, the first user provides input for setting properties (e.g., defining the media slots) for a template. Each media slot is assignable to a respective video or photo, with such assignments being made during the template usage phase,” in which, is the same as the Applicant’s claim language. Davidson discloses a generative image model in Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40. Moreover, the combination of Mahar and Davidson discloses the Applicant’s amended claim language in Paragraphs 0019; 0023; 0027; 0029 of Mahar.
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Moreover, the combination of Mahar and Davidson discloses the Applicant’s amended claim limitation in Paragraphs 0049; 0060 of Mahar.
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Moreover, Mahar disclosed the Applicant’s claim language of “as output, an image file representing the custom sticker” in Paragraphs 0020; 0061; 0077; 0094; 0098; 0192. MPEP § 2106 states Office personnel are to give claims their broadest reasonable interpretation in light of the supporting disclosure. In re Morris, 127 F.3d 1048, 1054-55, 44 USPQ2d 1023, 1027-28 (Fed Cir. 1997). Accordingly, the examiner maintains the rejection.
The Applicant alleged the following on pages 10-11 of the remarks: “The mapping the Examiner has constructed between the references and the claim elements is precise: Mahar supplies messaging and stickers, Davidson supplies the prompt template and generative language model. That precise correspondence, developed from the claim outward, is the hallmark of hindsight reconstruction. KSR cautioned that "a court must be careful not to allow hindsight reconstruction to supply a missing motivation." 550 U.S. at 421. The asserted rationale indistinguishable from rationales that could be advanced for combining any two AI references falls squarely within that caution. For at least the reasons set forth above, amended claims 1, 11, and 20 are not rendered obvious by Mahar in view of Davidson, and the rejection should be withdrawn.” The examiner is not persuaded. In this case, we find such a modification of an old process using prompts to incorporate a new system of prompt including an instruction to a generative language model to interpret the text to be obvious. In KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 417 (2007), the Supreme Court held that “if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill.” Id. at 417. “The combination of familiar elements according to known methods is likely to be obvious when it does no more than yield predictable results.” Id. at 416; see also id. at 417 (“If a person of ordinary skill can implement a predictable variation, § 103 likely bars its patentability.”); In re Schreiber, 128 F.3d 1473, 1477 (Fed. Cir. 1997) (“It is well settled that the recitation of a new intended use for an old product does not make a claim to that old product patentable.” (citations omitted)). We do not find that the evidence shows having a prompt including an instruction to a generative language model to interpret the text “uniquely challenging or difficult for one of ordinary skill in the art.” Leapfrog Enters., Inc. v. Fisher-Price, Inc., 485 F.3d 1157, 1162 (Fed. Cir. 2007) (citing KSR, 550 U.S. at 418). In addition, the references teaches features that are directed to analogous art and they are directed to the same field of endeavor, such as artificial intelligence. This close relation between the references highly suggests an expectation of success. Accordingly, we do not consider Applicants’ argument to sufficiently demonstrate the Examiner’s rejection is in error.
The Applicant alleged the following: “Claims 3, 5, 13, and 15 depend from amended claim 1 or amended claim 11 and incorporate all limitations thereof. The addition of Prasad does not remedy the deficiencies of the Mahar- Davidson combination identified above. Prasad describes AI-driven emoji prediction and rule-based term replacement; it does not disclose or suggest using text of a chat message composed by a user for transmission to another user as the seed text for a two-stage generative prompt pipeline that produces a custom sticker, and it does not supply the negative limitation that the request is received without separate user-provided image description. Applicant respectfully requests withdrawal of this rejection.” The examiner is not persuaded. The examiner asserts the combination of Mahar, Davidson and Prasad discloses prior to dynamically generating the first prompt in Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40 of Davidson. Moreover, Prasad discloses the Applicant’s claim language of “performing a content check on the text received with the request by comparing the text against a predefined list of objectionable words and phrases and discontinuing the processing of the request if the content check identifies any words or phrases, within the text, from the predefined list of objectionable words and phrases” in Column 17, Lines 59-67 & Column 18, Lines 1-15. Accordingly, the examiner maintains the rejection.
The Applicant alleged the following: “Claims 4, 9, 14, and 19 depend from amended claim 1 or amended claim 11 and incorporate all limitations thereof. The addition of Ghosh does not remedy the deficiencies of the base combination. Ghosh describes JSON-formatted data structures and certain generative image model architectures. Ghosh does not disclose or suggest the claimed flow in which chat-message text composed for human-to-human transmission drives a two-stage generative prompt pipeline. Applicant respectfully requests withdrawal of this rejection.” The examiner is not persuaded. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., human-to-human transmission drives a two-stage generative prompt pipeline) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Accordingly, the examiner maintains the rejection.
The Applicant alleged the following: “Claims 8 and 18 depend from amended claim 1 or amended claim 11 and incorporate all limitations thereof. SOARES discloses that a generative language model may be a Large Language Model accessible over a network. SOARES presupposes a functioning pipeline in which text input drives sticker generation through a language model. The base combination of Mahar and Davidson does not establish that pipeline for the reasons set forth above, and the addition of SOARES does not bridge the gap. Applicant respectfully requests withdrawal of this rejection.” The examiner is not persuaded. The combination of Mahar, Davidson and SOARES discloses generative language model is a Large Language Model (LLM) accessible to the server over a network in paragraphs 0041; 0063 of SOARES. In addition, the references teaches features that are directed to analogous art and they are directed to the same field of endeavor, such as creating customized graphics (i.e. images/stickers). This close relation between the references highly suggests an expectation of success. Accordingly, the examiner maintains the rejection.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 2, 6-7, 10-12 and 15-17 are rejected under 35 U.S.C. 103 as being unpatentable over Mahar, US Patent Application Publication No.: 20250047969 in view of Davidson, US Patent No.: 12153778.
Claim 1:
Mahar discloses a method performed by a server for generating a custom sticker in response to a request from a client device (See Mahar Abstract; Paragraphs 0020; 0061; 0077; 0094; 0098; 0192). Mahar failed to disclose prompt including an instruction to a generative language model to interpret the text. However, Davidson discloses the feature in Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have further modified Mahar by including prompt including an instruction to a generative language model to interpret the text, as taught by Davidson, to thereby create prompted text-to-image generation using artificial intelligence, more effectively (See Davidson Abstract; Field of Invention and Summary). In addition, the references teaches features that are directed to analogous art and they are directed to the same field of endeavor, such as artificial intelligence. This close relation between the references highly suggests an expectation of success.
As modified:
The combination of Mahar and Davidson discloses the following:
receiving the request from the client device, the request including text comprising a message input by a user of the client device (See Mahar Paragraphs 0019; 0023; 0027; 0029), into a message input field of a chat interface presented at the client device (See Mahar Paragraphs 0049; 0060), the message being composed by the user for transmitting to another user as a chat message via the chat interface (See Mahar Paragraphs 0049; 0060), the request being received without the user separately providing, via the chat interface (See Mahar Paragraphs 0049; 0060), any description of an image to be generated (See Mahar Paragraphs 0019; 0023; 0027; 0029; 0096);
and processing the request by:
dynamically generating a first prompt based on the text received with the request using a first predefined prompt template (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40), the first prompt including an instruction to a generative language model to interpret the text and generate (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40), as output, a textual description (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) of the custom sticker (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192);
providing the first prompt to a generative language model (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40), as input, and receiving from the generative language model, as output, the textual description (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) of the custom sticker (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192);
dynamically generating a second prompt to include the textual description (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) of the custom sticker (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192) using a second predefined prompt template, the second prompt (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) including an instruction to a generative image model to interpret the textual description (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) of the custom sticker (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192) and generate, as output, an image file representing the custom sticker (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192);
providing the second prompt (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) to the generative image model, as input, and receiving from the generative image model (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40), as output, an image file representing the custom sticker (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192);
and sending the image file representing the custom sticker to the client device for presentation (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192), in association with the message, within the chat interface (See Mahar Paragraphs 0019; 0023; 0027; 0029; 0049).
Claim 2:
The combination of Mahar and Davidson discloses prior to sending the image file to the client device, processing the image file by overlaying (See Mahar Paragraph 0039-0046) a caption onto an image of the image file, the caption derived to include the text input into the message input field of the chat interface (See Mahar Paragraphs 0049; 0060).
Claim 6:
The combination of Mahar and Davidson discloses wherein dynamically generating the second prompt (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) comprises: dynamically generating the second prompt (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) using the second predefined prompt template to include an input prompt specifying the textual description (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) of the custom sticker (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192), and a negative prompt specifying, as constraints, undesirable elements and characteristics to be excluded (See Davidson Column 9, Lines 28-35) from the image file representing the custom sticker (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192).
Claim 7:
The combination of Mahar and Davidson discloses wherein dynamically generating the second prompt further (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) comprises: dynamically generating the second prompt (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) using the second predefined prompt template(See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) to include one or more examples, each example comprising a textual description (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) of a sticker paired with an image file representing a sticker, as desired output (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192).
Claim 10:
The combination of Mahar and Davidson discloses wherein sending the custom sticker (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192) to the client device includes causing the client device to: present the custom sticker along with a plurality of other stickers within a sticker tray (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192) of the chat interface (See Mahar Paragraphs 0049; 0060), each sticker within the sticker tray user-selectable (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192) and, upon selection of a sticker in the sticker tray (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192), the selected sticker (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192) will populate the message input field of the client device, thereby enable a user to send the selected sticker (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192) to another user over a network by activating a send button in the chat interface (See Mahar Paragraphs 0049; 0060).
Claims 11, 12 and 16-17:
Claims 11, 12 and 16-17 are rejected on the same basis as claims 1, 2, 6-7 and 10.
Claim 20:
Claim 20 is rejected on the same basis as claim 1 and 10.
Claim(s) 3, 5, 13 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Mahar, US Patent Application Publication No.: 20250047969 in view of Davidson, US Patent No.: 12153778 and in further view of Prasad, US 12223121.
Claim 3:
The combination of Mahar and Davidson failed to disclose content check. However, this feature is disclosed in Column 17, Lines 59-67 & Column 18, Lines 1-15. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have further modified Mahar and Davidson by including content check, as taught by Prasad, to thereby analyze a plurality of factors associated with the inputs, more effectively (See Prasad Summary of the Invention). In addition, the references teaches features that are directed to analogous art and they are directed to the same field of endeavor, such as artificial intelligence. This close relation between the references highly suggests an expectation of success.
As modified:
The combination of Mahar, Davidson and Prasad discloses the following:
prior to dynamically generating the first prompt (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40), performing a content check (See Prasad Column 17, Lines 59-67 & Column 18, Lines 1-15) on the text received with the request by comparing the text against a predefined list of objectionable words and phrases (See Prasad Column 17, Lines 59-67 & Column 18, Lines 1-15); and discontinuing the processing of the request if the content check (See Prasad Column 17, Lines 59-67 & Column 18, Lines 1-15) identifies any words or phrases, within the text, from the predefined list of objectionable words and phrases (See Prasad Column 17, Lines 59-67 & Column 18, Lines 1-15).
Claim 5:
The combination of Mahar and Davidson discloses prior to dynamically generating the second prompt (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40), performing a content check (See Prasad Column 17, Lines 59-67 & Column 18, Lines 1-15) on the textual description of the custom sticker (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192) received as output from the generative language model (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40); and upon the content check passing (See Prasad Column 17, Lines 59-67 & Column 18, Lines 1-15), performing a rule-based term replacement process on the textual description of the custom sticker (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192) to replace specific words or phrases with alternative words or phrases, according to one or more predefined rules (See Prasad Column 17, Lines 59-67 & Column 18, Lines 1-15).
Claim 13:
Claim 13 is rejected on the same basis as claim 3.
Claim 15:
Claim 15 is rejected on the same basis as claim 5.
Claim(s) 4, 9, 14 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Mahar, US Patent Application Publication No.: 20250047969 in view of Davidson, US Patent No.: 12153778 and in further view of Ghosh, US 20240404225.
Claim 4:
The combination of Mahar and Davidson failed to explicitly disclose a JavaScript Object Notation (JSON) object. However, Ghosh discloses the feature in paragraph 0038. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have further modified Mahar and Davidson by including a JavaScript Object Notation (JSON) object, as taught by Ghosh, to thereby create a digital representation by offering a unique and customized presence in online spaces for more engaging and immersive digital experiences, more effectively (See Ghosh Background of the Invention). In addition, the references teaches features that are directed to analogous art and they are directed to the same field of endeavor, such as artificial intelligence. This close relation between the references highly suggests an expectation of success.
As modified:
The combination of Mahar, Davidson and Ghosh discloses the following:
wherein dynamically generating the first prompt (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) further comprises: dynamically generating the first prompt using the first predefined prompt template to include instructions to the generative language model (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) to format the output as a JavaScript Object Notation (JSON) object (See Ghosh Paragraph 038), the JSON object (See Ghosh Paragraph 038) to include i) the textual description of the custom sticker (See Mahar Paragraphs 0020; 0061; 0077; 0094; 0098; 0192), and ii) the text received with the request as input via the message input field of the chat interface (See Mahar Figure 13, Item 1316; Paragraphs 0191-0192).
Claim 9
The combination of Mahar, Davidson and Ghosh discloses the following:
wherein the generative image model (See Davidson Figure 1, Item 110; Column 1, Lines 15-67; Column 2, Lines 1-40; Column 7, Lines 57-60; Column 8, Lines 20-40) is selected from the group consisting of:
a Generative Adversarial Network (GAN), utilizing competing neural networks to generate image files with images that are visually similar to authentic images based on text-based prompts (See Ghosh Paragraph 0136);
a Variational Autoencoder (VAE), using a probabilistic approach to generate image files with images by encoding inputs into a latent space and then decoding the inputs back to outputs, guided by text-based prompts (See Ghosh Paragraphs 0251-0258);
and a Transformer-based model, designed for image generation by processing text-based prompts through self-attention mechanisms to produce image files with images (See Davidson Column 2, Lines 20-31).
Claim 14:
Claim 14 is rejected on the same basis as claim 4.
Claim 19:
Claim 19 is rejected on the same basis as claim 9.
Claim(s) 8 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Mahar, US Patent Application Publication No.: 20250047969 in view of Davidson, US Patent No.: 12153778 and in further view of SOARES, US 20250124624.
Claim 8:
The combination of Mahar and Davidson failed to disclose generative language model is a Large Language Model (LLM) accessible to the server over a network. However, SOARES discloses this feature in paragraphs 0041; 0063. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have further modified the combination of Mahar and Davidson by including generative language model is a Large Language Model (LLM), as taught by SOARES, to thereby quickly create and customize images using generative language models, more effectively (See SOARES Abstract). In addition, the references teaches features that are directed to analogous art and they are directed to the same field of endeavor, such as creating customized graphics (i.e. images/stickers). This close relation between the references highly suggests an expectation of success.
Claim 18:
Claim 18 is rejected on the same basis as claim 8.
Pertinent Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20240422113 relates to techniques for facilitating selection of stickers in the context of an interaction system that provides a messaging application or service.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHEREE N BROWN whose telephone number is (571)272-4229. The examiner can normally be reached M-F 5:30-2:00 PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, SAID BROOME can be reached at (571) 272-2931. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SHEREE N BROWN/Primary Examiner, Art Unit 2612 June 11, 2026
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